Analysis of the gene-protein interaction network in glioma

Zhou, Chao; Wj, Teng; Zhuang, Jing; Hl, Liu; Sf, Tang; Xj, Cao; Bn, Qin; Cc, Wang; Cg, Sun

doi:10.4238/2015.november.13.3

Cited by 9 publications

(9 citation statements)

References 40 publications

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“…Cytokine networks play important regulatory roles in inflammatory immune responses to cancer including glioma 39–41. Cytokines are also involved in chronic inflammation that may lead to carcinogenesis 39.…”

Section: Discussionmentioning

confidence: 99%

Leucine-rich glioma inactivated 3: integrative analyses support its prognostic role in glioma

Kwon¹,

Kim²,

Yun³

2017

OTT

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BackgroundLeucine-rich glioma inactivated 3 (LGI3) is a secreted protein member of LGI family. We previously reported that LGI3 was expressed in brain, adipose tissues and skin, where it played roles as a multifunctional cytokine. We postulated that LGI3 may be involved in cytokine network in cancers.AimThis study aimed to analyze differentially expressed genes in glioma tissues and glioma cohort data to investigate the prognostic role of LGI3 and its receptors.Materials and methodsExpression microarray data from Gene Expression Omnibus and glioma cohort data were analyzed using bioinformatic tools for statistical analysis, protein–protein interactions, functional enrichment and pathway analyses and prognostic association analysis.ResultsWe found that LGI3 and its receptors, ADAM22 and ADAM23, were significantly downregulated in glioma tissues. Eleven upregulated genes and two downregulated genes in glioma tissues were found to be the previously reported LGI3-regulated genes. Protein–protein interaction network analysis showed that 85% of the LGI3-regulated and glioma-altered genes formed a cluster of interaction network. Functional enrichment and Kyoto Encyclopedia of Genes and Genomes (KEGG) pathway analyses revealed the association of these genes with hypoxia responses, p53 and Akt signaling and various cancer-related pathways including glioma. Analysis of expression microarray data of glioma cohorts demonstrated that low expression levels of LGI3, ADAM22 and ADAM23 were significantly associated with poor prognosis of glioma.ConclusionThese results propose that LGI3 and its receptors may play a prognostic role in glioma.

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Section: Discussionmentioning

confidence: 99%

Leucine-rich glioma inactivated 3: integrative analyses support its prognostic role in glioma

Kwon¹,

Kim²,

Yun³

2017

OTT

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“…Human MEG3 is an imprinted DLK1-MEG3 locus gene and is located in chromosome 14q32. 37,38 MEG3 has previously been shown to mediate tumorigenesis through its interaction with miRNAs. MEG3 has been found in various normal tissues, but MEG3 expression is often absent in tumor tissues because of its gene deletion and promoter hypermethylation.…”

Section: Discussionmentioning

confidence: 99%

“…Human MEG3 is an imprinted DLK1‐MEG3 locus gene and is located in chromosome 14q32 . MEG3 has previously been shown to mediate tumorigenesis through its interaction with miRNAs.…”

Section: Discussionmentioning

confidence: 99%

Long noncoding RNA (MEG3) in urinal exosomes functions as a biomarker for the diagnosis of Hunner‐type interstitial cystitis (HIC)

Liu

Chen

Liu

et al. 2019

J of Cellular Biochemistry

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Background Toll‐like receptor‐7 (TLR7) is functionally involved in the pathogenesis of Hunner‐type interstitial cystitis (HIC). In addition, maternally expressed gene 3 (MEG3) is implicated in many urethral diseases. In this study, we aimed to verify the hypothesis that exosomal MEG3 in urine can be used as a novel diagnostic biomarker for HIC. Methods Electron microscopy was utilized to observe the distribution of urinary exosomes between the case group and the control group. Receiver operating characteristic analysis was utilized to compare the diagnostic values of MEG3 and miR‐19a‐3p. Computational analysis and luciferase assay were conducted to identify the correlation between MEG3 and miR‐19a‐3p as well as between TLR7 and miR‐19a‐3p. In addition, real‐time polymerase chain reaction and Western blot were performed to establish the signaling pathways implicated in the pathogenesis of HIC. Results When age and gender distributions are excluded, urinary exosomes were equally distributed between case and control groups. The area under the curve of MEG3 was larger than that of miR‐19a‐3p, indicating that MEG3 has a better value in the diagnosis of HIC. In addition, patients with HIC showed elevated MEG3 expression and inhibited miR‐19a‐3p expression, thus establishing a negative correlation between MEG3 and miR‐19a‐3p. MEG3 and TLR7 were both identified as targets of miR‐19a‐3p, establishing a MEG3/miR‐19a‐3p/TLR7 signaling pathway, in which MEG3 enhances the expression of TLR7 via inhibiting the expression of miR‐19a‐3p. Conclusion MEG3 level was upregulated in patients with HIC. In addition, MEG3 downregulated miR‐19a‐3p expression while upregulating TLR7 expression. Furthermore, MEG3 contributes to the pathogenesis of HIC. Therefore, exosomal MEG3 in urine can be used as a biomarker for HIC diagnosis.

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“…Wang et al integrated gene interaction information into a weighted random survival forest method to perform an accurate survival prediction and to discover a survival biomarker for glioma [ 5 ]. Zhou et al identified the glioma-specific protein interaction network based on bulk RNA-seq data and performed enrichment analysis to verify disease-specific molecular complexes [ 6 ]. Due to the complexity of glioma, more genetic markers need to be discovered.…”

Section: Introductionmentioning

confidence: 99%

Gene biomarker prediction in glioma by integrating scRNA-seq data and gene regulatory network

Qin

et al. 2021

BMC Med Genomics

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Background Although great efforts have been made to study the occurrence and development of glioma, the molecular mechanisms of glioma are still unclear. Single-cell sequencing technology provides a new perspective for researchers to explore the pathogens of tumors to further help make treatment and prognosis decisions for patients with tumors. Methods In this study, we proposed an algorithm framework to explore the molecular mechanisms of glioma by integrating single-cell gene expression profiles and gene regulatory relations. First, since there were great differences among malignant cells from different glioma samples, we analyzed the expression status of malignant cells for each sample, and then tumor consensus genes were identified by constructing and analyzing cell-specific networks. Second, to comprehensively analyze the characteristics of glioma, we integrated transcriptional regulatory relationships and consensus genes to construct a tumor-specific regulatory network. Third, we performed a hybrid clustering analysis to identify glioma cell types. Finally, candidate tumor gene biomarkers were identified based on cell types and known glioma-related genes. Results We got six identified cell types using the method we proposed and for these cell types, we performed functional and biological pathway enrichment analyses. The candidate tumor gene biomarkers were analyzed through survival analysis and verified using literature from PubMed. Conclusions The results showed that these candidate tumor gene biomarkers were closely related to glioma and could provide clues for the diagnosis and prognosis of patients with glioma. In addition, we found that four of the candidate tumor gene biomarkers (NDUFS5, NDUFA1, NDUFA13, and NDUFB8) belong to the NADH ubiquinone oxidoreductase subunit gene family, so we inferred that this gene family may be strongly related to glioma.

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Analysis of the gene-protein interaction network in glioma

Cited by 9 publications

References 40 publications

Leucine-rich glioma inactivated 3: integrative analyses support its prognostic role in glioma

Leucine-rich glioma inactivated 3: integrative analyses support its prognostic role in glioma

Long noncoding RNA (MEG3) in urinal exosomes functions as a biomarker for the diagnosis of Hunner‐type interstitial cystitis (HIC)

Gene biomarker prediction in glioma by integrating scRNA-seq data and gene regulatory network

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